Artificial Intelligence (AI) has transformed healthcare by improving customized medical care, accurate diagnosis, and follow-up plans, and during the COVID-19 pandemic, AI models have been used to predict symptoms, understand the treatment, and virus spread, and expedite research using medical data. However, fragmented patient data and privacy concerns pose challenges for creating and implementing robust AI models in real-world settings. This research paper proposes a novel solution that utilizes blockchain and AI technologies to address these challenges. Blockchain provides secure and transparent data access, ensuring privacy and data integrity, while AI-based federated learning enables training models on decentralized data sources, reducing the risk of information breaches and creating robust AI models that can generalize across different datasets. The proposed solution offers several benefits, including privacy-preserving AI models that can be developed and implemented without centralized data access. The blockchain-based secure data access ensures transparency, immutability, and traceability, reducing the risk of data tampering. In conclusion, combining these technologies can revolutionize healthcare by improving patient outcomes through privacy-preserving access to decentralized data and creating robust AI models. This paper provides a framework for building a secure and resilient healthcare system leveraging AI, blockchain, and federated learning. Further research is necessary to assess the feasibility of implementing the proposed solution on a large scale.